realclimate and Disinformation on UHI

Those global data sets are contaminated by the fact that two-thirds of the globe’s stations dropped out in 1990. Most of them rural and they performed no urban adjustment. And, Lou, you know, and the people in your studio know that if they live in the suburbs of New York City, it’s a lot colder in rural areas than in the city. Now we have more urban effect in those numbers reflecting — that show up in that enhanced or exaggerated warming in the global data set.

D’Aleo is misdirecting through his teeth here. … he also knows that urban heat island effects are corrected for in the surface records, and he also knows that this doesn’t effect ocean temperatures, and that the station dropping out doesn’t affect the trends at all (you can do the same analysis with only stations that remained and it makes no difference). Pure disinformation.

Later in the comments (#167), an RC reader inquired about UHI adjustments, noting the lack of discusison of this point as follows:

#167/ In all of the above posts there is no mention of the urban heat island effect, nor of the effect of rural station drop out nor of the effect the GISS data manipulation has on surface temperature. Why is that?

To which Gavin replied:

[Response: Because each of these ‘issues’ are non-issues, simply brought up to make people like you think there is something wrong. The UHI effect is real enough, but it is corrected for - and in any case cannot effect ocean temperatures, retreating glaciers or phenological changes (all of which confirm significant warming). The station drop out ‘effect’ is just fake, and if you don’t like GISS, then use another analysis – it doesn’t matter. – gavin]

Neither CRU nor NOAA have archived any source code for their calculations, so it is impossible to know for sure exactly what they do. However, I am unaware of any published documents by either of these agencies that indicate that they “correct” their temperature index for UHI effect (as Gavin claims here) and so I’m puzzled as to how Gavin expects D’Aleo to be able to “know” that they carry out such corrections. And as to GISS adjustments, as we’ve discussed here in the past (and I’ll review briefly), outside the US, they have the odd situation where “negative UHI adjustments” are as common as “positive UHI adjustments”, raising serious questions about whether the method accomplishes anything at all, as opposed to simply being a Marvelous Toy.
CRU Urban Adjustments?

The most recent exposition of CRU methodology is Brohan et al 2006, which stated in respect to UHI that they included an allowance of 0.1 deg C/century in the uncertainty, but does not describe any “correction” to the reported average temperature:

The previous analysis of urbanisation effects in the HadCRUT dataset [Folland et al., 2001] recommended a 1 sigma uncertainty which increased from 0 in 1900 to 0.05 deg C in 1990 (linearly extrapolated after 1990) [Jones et al., 1990]. … To make an urbanisation assessment for all the stations used in the HadCRUT dataset would require suitable meta-data for each station for the whole period since 1850. No such complete meta-data are available, so in this analysis the same value for urbanisation uncertainty is used as in the previous analysis [Folland et al., GRL 2001]; that is, a 1 sigma value of 0.0055 deg C/decade, starting in 1900… The same value is used over the whole land surface, and it is one-sided: recent temperatures may be too high due to urbanisation, but they will not be too low.

For greater certainty that CRU makes no “correction” for UHI in the actual temperature (only an allowance in the “uncertainty”), Folland et al (GRL 2001) stated:

We add independent uncertainties due to urbanisation, changing land-based observing practices and SST bias corrections. … The uncertainties given by RSOA due to data gaps and random errors (Figure 1a) were augmented using published estimates of global uncertainties associated with urbanization effects (e.g. Jones et al., 1990),…We assume that the global average LAT uncertainty increased from zero in 1900 to 0.1°C in 1990 (Jones et al, 1990), a value we extrapolate to 0.12°C in 2000 (Figure 1a).

Both sources clearly stated that they allow for UHI only by a slight increase in their uncertainty factor. Note that even this estimate relies on Jones et al 1990, a study which has been discussed at CA preciously. After Jones refused for years to identify the stations used in the 1990 study, FOI actions obtained this information. We discussed Jones et al 1990 in a number of posts. We observed here that Jones et al 1990 made untrue claims on the quality control for their Chinese network (the falseness of which would rise to misconduct in many fields). Jones et al 1990 described their QC procedures for Chinese stations as follows:

The stations were selected on the basis of station history; we selected those with few, if any changes in instrumentation, location or observation times.

I observed at the time that I had been able to track down third-party documentation on stations used in Jones’ China network and that it was “impossible that Jones et al could have carried out the claimed QC procedures.” Doug Keenan followed up on this with a complaint against Wang. As I recall, part of Wang’s defence was that the station histories consulted in 1990 had now been “lost”. So station histories – documents that had survived World War II, the Communist Revolution, the Great Leap Forward, carefully preserved by diligent clerks – were lost or destroyed by climate scientists under the IPCC regime. Hard to believe.

Be that as it may, Brohan et al 2006 does not say that they make any “correction” to their records for UHI, only that they make a slight increase in “uncertainty” – a completely different thing even in Gavin-World.

NOAA UHI Adjustments
The homepage for the NOAA temperature index is here. It cites Smith and Reynolds (2005) as authority. Smith and Reynolds, in turn, state that they use the identical procedure as CRU, i.e. they make an allowance in uncertainty, but do not correct the temperature index itself.

For LST [land surface temperatures] , bias errors may be caused by urbanization over the twentieth century, and uncertainty due to the use of nonstandard thermometer shelters before 1950 (Jones et al. 1990; Parker 1994; Folland et al. 2001). Here we use the LST bias uncertainty estimates of Folland et al. (2001).

GISS U.S. Adjustments
Unlike CRU and NOAA, GISS makes a decent effort to adjust for UHI in the U.S. (outside the USA, its efforts are risible.) A few days ago, I showed the notable difference between the GISS (UHI-adjusted) version in the US and the NOAA unadjusted version, where the difference is much more than 0.1 deg C/century asserted by CRU/NOAA.

surfacestations.org has made a concerted effort to identify high-quality stations within the USHCN network (CRN1-2 stations) and preliminary indications are that the GISS U.S. estimate will not differ greatly from results from the “best” stations (though there will probably be a little bias.)

This does not prove that CRU and NOAA estimates are any good. Quite the contrary. It shows that the CRU and NOAA failures to make UHI adjustments along the lines of GISS are introducing a substantial bias in these records.

GISS ROW Adjustments
Last year, I reviewed GISS adjustments outside the US in a series of posts. These adjustments are pig’s breakfast. In many cases, GISS makes UHI adjustments the “wrong” way” i.e. their adjustments presume a UHI cooling effect. These goofy results are mentioned passim by Hansen as “false local adjustments”. At the end of the day, there is no evidence that Hansen’s “UHI” adjustments outside the U.S. even begin to deal with the problem. Posts were herehereherehereherehere.

The difference between the US and ROW arises because the US has a fairly unique backbone of long relatively rural stations (the USHCN network), where, despite all the barbecues and air conditioners and parking lots, an attempt has been made at having weather stations located at non-airport non-urban locations. GISS uses nightlights information to subset this data and to choose a subset as a trend reference. There’s lots to dislike in the execution, but the intent makes sense.

Outside the US, there is no corresponding network. A lot of the stations are in cities and virtually all of the recent data (post-1990) is from airports. GISS uses hopelessly obsolete population meta-data to supposedly identify “rural” stations, but GISS “rural” is all too often small city (or even large city). Unlike the US, GISS methods don’t find sure ground and thus their adjustments end up being essentially random, mostly reflecting random site relocations and having nothing to do with UHI adjustment. They may say that they adjust for UHI, but this cannot be demonstrated in their actual adjustment, which throws up nonsensical wrong-way adjustments. Even Hansen acknowledges the wrong-way adjustments as being a problem:

it is difficult to have confidence in the use of urban records for estimating climate change…some urban stations show little or no warming, even a slight cooling relative to rural neighbors. Such results can be a real systematic effect e.g. cooling by planted vegetation or the movement of a thermometer away from the urban center or a random effect of unforced regional variability and measurement errors. Another consideration is that even rural locations may contain some anthropogenic warming.

And CRU and NOAA don’t even bother.

“urban heat island effects are corrected for in the surface records”
Contrary to Gavin’s assertion, there is no evidence that CRU or NOAA correct their records for urban heat island effects. They make a very slight allowance in their “uncertainty” for UHI relying ultimately on an estimate made in Jones et al 1990, a study which made untrue (and impossible) claims about quality control steps.

The only network where a plausible adjustment is made is the GISS US network (representing less than 2% of the world’s surface, as NASA GISS reminds us.) While GISS US results are plausible, outside the US, the GISS adjustment is a pig’s breakfast and no sane person can claim that they live up to the warranty. What makes this frustrating is that the US temperature history (GISS version) had 1934 as a record year – a result that was at variance with the other indices and other parts of the world. Is this because this is the only network/country combination with an effective UHI adjustment or because of a unique “regional” climate history in the US?

Whether or not urban heat islands have a material impact on the surface records is a different question. The difference between GISS US results and NOAA US results is strong evidence that there is a noticeable impact – one which needs to be addressed by CRU and NOAA and by GISS outside the US. In my opinion, Gavin’s own statement that “urban heat island effects are corrected for in the surface records” is, to borrow a phrase from realclimate, “disinformation”.

For the record, I think that Gavin was entitled to complain about the lack of balance or representativeness in the Lou Dobbs panel: whether D’Aleo, Lehr and Wissner-Gross are right or wrong about their points, they are completely unrepresentative of the mainstream climate community, which is surely entitled to complain on that count. My not discussing their solar views here doesn’t mean that I endorse them – Gavin Schmidt and his colleagues spend time deconstructing such analyses; solar proponents should pay attention to criticism regardless of the quarter from which it originates; given that others do such analyses, I think that my time is better spent on issues not covered elsewhere. The fact that there is a legitimate complaint against the construction of the Lou Dobbs panel doesn’t mean that Schmidt should make untrue claims about what CRU and NOAA do in their construction of surface records.

134 Comments

I have found the work at Surfacestations.org to be extremely illuminating when you look at the exact conditions of a weather station versus what Nasa/Noaa does with outdated satellite information. Based on what I have seen, it’s impossible for Nasa to unwrap the UHI from individual stations without knowing the actual conditions at a site. Adjusting them based off their neighboring sites would be acceptable if the whole system wasn’t fraught with the same or similar difficulties.

What was the figure that the GISS said that they applied to quality of this system? 10 hours a month? Frankly, it’s a joke. With the Surface Stations being necessary to prove the correlation and the unrealistic adjustments that are made irrespective to the individual stations condition, I wouldn’t be surprised to see if an honest attempt wouldn’t weaken the CO2/Temperature correlation.

Keep up the good work you and Anthony do as it’s how science is supposed to be done (Transparent, repeatable, honest, and humble).

Can someone give a summary of the situation on disclosure from Hansen, GISS, etc… on their methods and datasets. I read that Hansen begrudgingly disclosed some source code, but apparently it wasn’t for UHI. What have they disclosed, and what have they not disclosed? Is the info from Phil Jones still a secret? What is the status on the info that they have disclosed? Is it all a rat’s nest that auditors are still trying to decipher? This would make a great bit of info for a journalist to note.

Steve: To my knowledge, Hansen’s (grudgingly) disclosed all his code. On the left frame, there are Categories including Surface Record. If you browse through past posts, you’ll get a sense of where things stand for individual data sets. But briefly, neither CRU nor NOAA have archived line 1 of their source code.

I’m thinking about having a look at ROW stations and developing an independent temperature reconstruction. (I’m looking for interesting projects for learning R and/or F#). Do you have any suggestions for how one could go about identifying rural and urban stations outside the USA? Off the top of my head all I can think of is using Google Earth, but I doubt that would be adequate. Any other suggestions? Thanks.

Steve: I suggest starting with a defined region and simply look up the stations one by one. That’s what I did with Peru, for example. Why don’t you start with Peru – it’s large enough to be non-trivial, but small enough that it doesn’t take all that long to look up stations one by one. Plus you can use some of the past posts as guides for some oddities in the names e.g. Puerto Maldon [ado].

#7. Homogeneity adjustment is different from UHI adjustment. I re-read Peterson and Vose 1997 to double-check this point and they do not describe a UHI adjustment of the type carried out by GISS in the US (which seems like the minimum requirement). Further proof that NOAA does not do a UHI adjustment is simply the difference between the NOAA U.S. and the GISS U.S. series: GISS does a HI adjustment and has a markedly lower trend than NOAA since 1940. That is convincing evidence for me that the GISS U.S. adjustment for UHI does something that NOAA doesn’t.

Steve,
(My apologies if I’m repeating an oft-asked & oft-answered question here)…I am highly dubious of any model’s ability to ‘correct’ for UHI, be it on a site-specific, regional, or global basis. It seems to me that the only non-UHI-biased temperatures are going to be historically & presently rural (incl. ocean). Is there a temperature graph plotting strictly rural sites over the last, say, 100 years? I’ve seen individual sites, but not US-in-aggregate. Thanks!

Clarification: Ideally, that temperature graph would be raw data. I found the EPA study on Rural & Urban Trends in Proximity to Large Cities, but am skeptical of the ‘purity’ of the data feeding it. Thanks!

Perhaps, but the homogeneity adjustment supposedly takes into account metadata such as population and location, and changes in instrument environment. This homogeneity adjust could account for some of the divergence between NOAA and NASA.

I believe it is important to distinguish between UHI effects on the temperature record and the “micro-site” effects that Anthony Watts is surveying at surfacestations.org. A completely rural station can still have serious micro-site issues from a nearby parking lot or air conditioner. An urban station can have excellent micro-siting (as in a city park) even in the middle of a large urban heat island.

I have yet to see any methodical study looking at both of these effects. Has anyone else seen one?

And then you have the situation of a temperature sensor mounted over an air-conditioning system on a building rooftop in the middle of a city (actual site that Watts found). Don’t remember where it was right now. How do you figure an adjustment for that!

The real problem in all of this is the data … period. Even ocean temperatures.

I can’t remember which article I read, but they explained the problems with early sea temperature data – they would drop buckets in the water, pull them up, and measure the temp. Some bags were skins, others wooden. This leads to problems in measurement.

Of course, they make “adjustments” to the data to compensate – and we must assume the adjustments are valid and correct and compensate for the differences properly.

To hear it from the climate modelers – there’s not anything that is not properly adjusted for.

Are either of these ‘corrections,’ UHI or microsite, applied to the surface values at the 50 or so stations where radiosondes are launched? And if so, wouldn’t that change the heights calculated at all standard and significant levels right up the line?

Aren’t there enough known rural sites in the network to allow the discarding of obviously urban stations so as not to have to worry about “adjustment” for UHI? The fact that “urban” stations are included for purposes of global climate monitoring seems rather dim-witted when there should be plenty of rural, or at least less urban, stations relatively nearby.

To make an urbanisation assessment for all the stations used in the HadCRUT dataset would require suitable meta-data for each station for the whole period since 1850. No such complete meta-data are available,

Hey, why not start now? Surfacestations.org has done a good deal of the job for you. Or better yet, ENFORCE YOUR OWN STANDARDS!!!

Here’s the thing about this. Hansen shows the adjustments for both Phoenix and Tokyo in the graphs in the 1999 paper. I checked his adjustments for Tokyo in the 1999 paper compared to the GISS adjustments currently for Tokyo. Not surprisingly, the current GISS homogenized data shows a steeper trend now than in the 1999 paper. (Just overlay the temperatures prior to 1950 and you’ll see about a 0.4C difference).

Obviously the homogenization adjustments changed since 1999.

Furthermore, the manner in which the UHI adjustment is made is very suspect. Hansen shows in the 1999 paper how the adjustment is made – with a linear adjustment trending towards zero in the present. But this can’t be right – because that would mean that in the present, there is no adjustment. Shouldn’t the adjustment be a step function, and not linearly decreasing?

Bizarre.
How can anyone rely on the GISS products? The UHI effects are adjusted but with no real rhyme or reason as to

Here’s the thing about this. Hansen shows the adjustments for both Phoenix and Tokyo in the graphs in the 1999 paper. I checked his adjustments for Tokyo in the 1999 paper compared to the GISS adjustments currently for Tokyo. Not surprisingly, the current GISS homogenized data shows a steeper trend now than in the 1999 paper. (Just overlay the temperatures prior to 1950 and you’ll see about a 0.4C difference).

Obviously the homogenization adjustments changed since 1999.

Furthermore, the manner in which the UHI adjustment is made is very suspect. Hansen shows in the 1999 paper how the adjustment is made – with a linear adjustment trending towards zero in the present. But this can’t be right – because that would mean that in the present, there is no adjustment. Shouldn’t the adjustment be a step function, and not linearly decreasing?

Bizarre.

How can anyone rely on the GISS products? The UHI effects are adjusted but with no real rhyme or reason as to the method, and no explanation as to how no adjustment in the present is a valid adjustment.

D’Aleo is misdirecting through his teeth here. … he also knows that urban heat island effects are corrected for in the surface records, and he also knows that this doesn’t effect ocean temperatures,

The part about not “effecting” ocean temperature may be in error, too, with regards to the GISS estimate of global temperature.

GISS uses smoothing in their global analysis. They smooth land temperature onto adjacent ocean but, as they note on their map page

Note: Ocean data are not used over land nor within 100km of a reporting land station.

I take that to mean that GISS does not smooth ocean temperature onto adjacent land. This gives the land a disproportionate effect on the global temperature estimate. (Note that the standard GISS smoothing radius is 1200 km, which is not small.)

GISS also does not use ocean data within 100km of land, including island stations. That, too, expands the effect of land temperature on the global estimate, including expanding the effect of any UHI bias.

I really don’t understand the point of arguing about UHI adjustments, when such adjustments are fundamentally not scientific. If your data is contaminated by an effect you cannot control, you discard it – you don’t get to “adjust” it. I cannot imagine such arguments being carried out amongst experimental particle physicists for example.

Suppose a particle physicist ran an experiment on a particle accelerator and collected data that were clearly incorrect. Upon further examination he determines that if the voltage on a particular deflector magnet had varied during the experiment it could cause a similar effect, and is able to convincingly model the effect of the voltage drift on the outcome. The result, he claims, is that he’s now measured the mass of particle X to the highest degree of accuracy ever. Hoorah!

He may be right, but no such result could ever by anything but provisional. Such a result would probably not even be publishable. At best he might be able to convince his funding source to give him a second chance at replication.

Our proxy analysis of the station data shows that Gavin’s claim cannot be true. The CRU and NCDC surface plots are generated from station data using a complicated procedure involving a reference grid. But the reference grid is not necessary to obtain their plot. It’s one of those complications that drops out if you look at the problem in another way. By taking the derivative of temperature with time at each station, summing all existing derivatives each year, and integrating, you obtain an almost identical plot to CRU, as you can see here in our Home Analysis section.

When the magnitude of adjustments you make to a data set is the same magnitude as the trend you are perpetuating then the data is at best highly questionable. Most people think that the global temperature record is a given as something as simple as temperature reading couldn’t possibly be wrong could it? Most people don’t realise that you have to correct for change in time of measurement, change in location, stations closing, urbanisation, and even MISSING DATA! Then to make these adjustments you have to battle with incomplete and missing station history records, lack of uniformity in measurement methodology and out of date station information.
The question I want to ask is, can we really construct a global temperature curve from 1900 to present? With so much data, with so many uncontrolled variables and unknowns the answer for me is a resounding NO! I think temperature records have to be assessed on a country by country (or cotenant by cotenant) basis and then these have to be evaluated individually to say ‘can we distinguish a significant warming trend’?
Here in sunny Australia most of our temperature records, particularly in rural stations only run to 1992, and you’d only be able to get sufficient data back to about 1930. However if we were going to construct an accurate historic temperature trend for Australia then we can only really settle for constructing it between those two years. Surely however that is enough to confirm any warming that may or may not be due to anthropogenic CO2 emissions. Also in constructing that record we can only pick stations that have been in the same rural location since 1930. That limits the data a lot but a least we could have some confidence in what we were looking at. I’d rather have two hundred correct data sets than 5000 wrong ones.
I believe a one size fits all global temperature record just cannot be constructed if we are really being honest.

Re: Alex B (#32), There are still a good number of rural Australian stations reporting up to the present day. They only disappeared from GISS because GISS couldn’t be bothered collating that data after 1992. Out of about 500 Australian stations to be found on the GISS database, only one is a completely rural mainland station with a continuous record from 1930 to 2008 (Cape Leeuwin).

GISS’s Australian station drop outs in the 1990s were predominantly rural, so the UHI problem becomes even more important. But the stations are still there and reporting; GISS just ignores them now.

Re: braddles (#36), Thanks for the reply. Though I can still only download data to 1992 for the station you mentioned from the GISS website, unless I am to believe a massive global warming to 999.9degC ;). Do you know how to get data beyond then? I guess we’re not very important down here in the bottom corner.

Cape Leeuwin, SW tip of West Australia, has 99% complete daily surface Tmax and Tmin starting 1907, station number Australia 9518. It is available on a CD from the Bureau of Meteorology, or from the site

The latter gives a lot of other weather data for each day and is current to about today.

The problem is not one of gathering the data so much as seeing that it gets into the global estimates in the form it deserves. The data above are sold as “raw”. What GISS or anyone else does is not known precisely by me.

I have a scientific project (no social commentary) almost complete from Australia doing just that. My email is sherro1@optusnet.com.au

Google Earth is most useful as a pictorial guide, but does not always have good distance measurement capability. In any case, the main modern Australian weather stations are photographed on ground – see one at Tennant Creek at

JoshV: There is a difference between your example – direct observation – and inferred measurements. The global temperature anomaly cannot be directly measured. There is no practical way to actually observe the heat content of the atmosphere, land, and oceans within [insert distance here] of the surface. Instead, you must make inferences based on individual data points. To put it in the context of a physics example, astronomers and cosmologists do similar types of adjustments all the time.
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Whenever you model something, you’ve simplified the system. The global temperature anomaly calculation is based on a model that breaks up the earth’s surface into a grid, performs a calculation to obtain an anomaly value for the grid based on a bunch of individual data points, and then puts everything together. The result is an inferred value that cannot be directly measured (like the mass of a galaxy, or the mass content of the universe).
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Whenever you simplify a system, you introduce error. The goal of “adjustments” is to find a systematic way to account for that error. This is quite common.
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The inexplicable tolerance in climatology for large errors, large uncertainties in climate parameters, and non-rigorous “adjustments” when compared to the signal (AGW) is a bit of a mystery to me, however. :)

Well, I was just talking about the adjustments, but I also consider the metric “global average temperature” to be fundamentally ill-defined and not at all scientific.

“Instead, you must make inferences based on individual data points. To put it in the context of a physics example, astronomers and cosmologists do similar types of adjustments all the time.”

Please give an example of this. The Hubble telescope was put in orbit with a very precise error in it’s main mirror, and to a certain extent the image aberrations caused by this error could be corrected with a computer model of the mirror’s anomaly. They still flew up the equivalent of Hubble spectacles to correct the issue at the source.

“Whenever you model something, you’ve simplified the system. The global temperature anomaly calculation is based on a model that breaks up the earth’s surface into a grid, performs a calculation to obtain an anomaly value for the grid based on a bunch of individual data points, and then puts everything together. The result is an inferred value that cannot be directly measured (like the mass of a galaxy, or the mass content of the universe).”

The mass content of the universe, if ever mentioned, is gross speculation – and any cosmologist will admit that it could be wildly inaccurate. As for the mass of galaxies – I think most physicists will readily admit that such measurements are highly provisional, subject to large error bars, and reliant on assumptions that could possibly be invalidated in the future.

“Whenever you simplify a system, you introduce error. The goal of “adjustments” is to find a systematic way to account for that error. This is quite common.”

Simplifying the system is called modeling. I am not talking about GCMs. I am talking about direct measurements of temperature – actual data, being “adjusted”. So even though a real world, calibrated instrument said it was 20 degC at lat x/lon y on Jan 19, 1978 at 1pm – we come up with an adjustment that says the temperature was actually 22 degC. Barring some sort of method of creating reproducible controlled experiments comparing the exact same temperature station, at the exact same time, with and without a city around it, there is no possible scientific basis for making such an adjustment.

The simplest solution it to throw out data that may be corrupted with UHI, and attempt to take measurements in places that are not subject to the effect.

Re: joshv (#35), I gave examples (mass of universe/galaxies) and can add more: age of the universe, age of stars, fusion sequences within stars, elemental makeup of different regions of a star, galactic rotation speeds, ~3K background radiation . . . there’s lots. In all cases, the instrumental record is adjusted based on a model.
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A model isn’t just a GCM. The way the earth is broken up for determining the global anomaly is a model. The way temperatures are used within the grids is a model. When you’re dealing with models, you automatically cede exactness. Models always introduce error. You correct for errors with adjustments. This is done all the time, in every major scientific field. Sometimes the model and adjustments can be hypothesis tested. Other times they cannot.
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You missed the point.
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The mass content of the universe, if ever mentioned, is gross speculation – and any cosmologist will admit that it could be wildly inaccurate. As for the mass of galaxies – I think most physicists will readily admit that such measurements are highly provisional, subject to large error bars, and reliant on assumptions that could possibly be invalidated in the future.

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Exactly. That’s why I gave those examples. That’s what happens when your data is inferred. That’s what happens with global anomalies. The fact that the field of climatology is reluctant to admit how large the potential errors are is what is wrong . . . not the fact that it uses inferred measurements and proxies and models, which are all legitimate scientific tools.

My point is that physicists don’t “adjust” their observations. You make an observation, which has a certain error level, and through an inferential chain of logic and mathematics derive another quantity which cannot be directly measured. If you get the “wrong” answer (whatever that means) you can’t go back and add an adjustment factor to the data you measured. See the Hubble example. Yes, you could computer correct the images generated by the faulty mirror, but this is effectively creating data that didn’t exist. You’d never know if your observations were correct or the result of the computer correction. So they flew up correcting mirrors that were inserted directly into the light path of the telescope, correcting the aberration at the source.

Climate scientists on the other hand create an ill-defined statistical metric, and then freely manipulate the input data. This would never pass muster in the hard sciences.

See the Hubble example. Yes, you could computer correct the images generated by the faulty mirror, but this is effectively creating data that didn’t exist.

In spite of what you see on TV, (CSI, etc.) There is, in fact, no way to mathematically retrieve a true unknown image from an out of focus image. IIRC, it falls into the category of ill-posed inverse problems even if, as in the case of the Hubble, you know exactly what caused the problem. They could clean the images up a little, but not to anything near the design resolution. That’s also why they use real time adaptive optics for the new large ground based telescopes (Keck, e.g.) to correct for atmospheric aberration.

In fact, there were so many problems with the Hubble (solar panel, gyros, etc.) that if they hadn’t had the optics issue to justify a repair mission, it probably would have failed after only a few months of operation.

Central England temperature derivation described here:http://hadobs.metoffice.com/hadcet/Parker_etalIJOC1992_dailyCET.pdf
from the document.
6. CONCLUSION
We have used a rather diverse set of stations to build on Manley’s work and create a daily mean CET series for
1772 to date. Our daily series is one of the longest available, but it cannot at present he based on an entirely
satisfactory set of stations. This is unfortunate since the monthly CET record is the longest available
instrumental temperature record in the world. The uncertainties involved in the replacement of Stonyhurst,
and the evidence for urban warming at several of our stations, lead us to stress the importance of the
establishment of guaranteed reference-stations for monitoring climatic variability and change. The stations
should be ‘guaranteed’ by according them special protection from closure or from serious local disturbances,
such as a major building within a few hundred metres. If the stations are in areas where progressive
urbanization is unavoidable, rural stations should be established as cross-checks. If the site is to be moved,
even by a short distance, observations should be made in parallel at both sites for at least 1 year, preferably longer

The best argument to make is the most conservative one, which is the argument that Steve is making. Otherwise, your “opponent” will focus on the weakest link in your position and ignore everything else. JohnV demonstrated here sometime ago, working with top-rated stations (rated by surface-stations), that GISS does a reasonable job of adjusting for UHI and Steve seems to agree in this post. This makes 1934, not 1998, the warmest year on record and the 1930’s the equivalent of the recent warm peak in the U.S. The ROW is a completely different story, allowing RC to dismiss the U.S. record as “only applying to 2% of the world”. This is the point that needs to be driven home.

Micro-site issues are interesting and worthy of study, but they aren’t going to substantially change anything. Claims that a world temperature doesn’t exist or can’t be measured may contain some truth, but they aren’t going to advance the debate.

Claiming that UHI “doesn’t matter” or that “UHI has been accounted for” without ever revealing exactly HOW it has been adjusted for and not openly debating the algorithms (or lack therof) is the problem.

If the AGW proponents ever released their data and methods and engaged in a scientific debate over them, they would make some headway with me. As it is, their behavior makes me doubt anything they say.

#43. This is interesting. For some time, we’ve been satirizing NASA’s inability to locate data that can be found on the internet. Cape Leeuwin is an example: data has myseriously started re-appearing in Nov 2008 after a gap of 8 years

Cape Otway is another example. Data collection stopped in 1992 and has suddenly started again in Nov 2008.

The data re-emerged at GHCN (interestingly one month after we discussed their Russian error). I haven’t seen a word of explanation at GHCN about the return of the prodigal son. I wonder if they’re having a feast.

As I recall, part of Wang’s defence was that the station histories consulted in 1990 had now been “lost”. So station histories – documents that had survived World War II, the Communist Revolution, the Great Leap Forward, carefully preserved by diligent clerks – were lost or destroyed by climate scientists under the IPCC regime. Hard to believe.

I am a long time lurker; I may have posted 2 or 3 times since CA began. I don’t claim any special knowledge of statistics or climatology, so sometimes the discussions here are more difficult for me to follow than others, yet I nonetheless often find myself reading CA when I should be doing something else.

Apparently, I missed the previous discussion of Chinese weather station data. It boggles the mind that climatologists treat historical data from the former Soviet Union and China as if the numbers had meaning.

I have spent a great deal of time in Eastern European archives and geographical institutes. So, I can fairly extrapolate that even if trustworthy weather data had been generated between 1914 and 1956, much of it was certainly lost. More to the point, trustworthy data was not generated. That is a certainty. Pretending that the Soviet and Chinese weather data are trustworthy is an exercise in self-deceit, and nothing more.

I’m curious. There seems to be a great deal of concern over station quality, the UHI, etc. On the other hand I am under the impression that John V.’s work has closed the issue on accuracy, trend lines, and the official US record.

As far as I understand John V’s work, the book is not closed. (Steve McIntyre is taking a conservative approach in cautioning that John V’s work may vindicate GISS’s UHI adjustment in the U.S., and such a conservative approach can be prudent.) However, the book is not closed. Some worthwhile reading can be done on http://global-warming.accuweather.com/2008/02/poor_location_equals_poor_data_1.html and look for Damo’s comments on John V.

My paper about this in Energy & Env. [2007] also discusses other studies on Chinese UHI effects. In particular, Ren et al. [GRL, 2007] concluded that a large part of the warming that has been measured in China is due to UHI.

Imagine James Bond is chasing an evildoer on the roofs of the carriages of the Orient Express. You are Agent 006 and have a GPS tag on him. Can you tell from that EXACTLY how fast the train is going? You would have to find out if 007 is chasing towards the front or back end of the train. Or how fast he is going – does he run at the “average” human speed or, being a superhero, does he go twice as fast? Is he injured and the villain is getting away? In short you can’t tell exactly how fast the train is going. Unless 007 reports back to HQ and recalls his story.
Same story with UHI. You can not correct for what you don’t know. You have to throw all urban stations out where you suspect UHI. Unless you send Anthony Watts out doing daily traverses across town (see his Reno post). The you would know, because you have measured UHI.

Gavin dismisses the dropout of rural stations in 1990 by saying you can include them and it doesn’t matter. But who has done such a study? No one. Since mostly rural stations were lost and a huge number of them in siberia/china where the big red hot spot sits, it is not a huge leap to see a geographic signature of the loss of these stations. To dismiss this effect as if it were well-studied goes beyond disengenuous.

Steve:
I aksed Gavin Schmidt who pointed me to:http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#urbanization,
at least with respect to NOAA’s treatment of urbanization effects (an algorithm to account for step-type changes and trend changes). I also understood him to say generally that there is “plenty of evidence that there is no substantial UHI effect in any of the large scale indices (Parker, 2004; 2006; ocean changes, glacier retreat etc)”.

Re: BRIAN M FLYNN (#61), Gavin cites glacier retreat as supporting the lack of UHI effect. Huh? Glaciers have a huge lag time and you can only detect changes in their length over many many decades. The warming of interest to AGW is from about 1980 to 1997 or 2000 and there is no way to detect this with glaciers. Parker is a silly reference to “no UHI effect” and is countered by a number of studies showing strong UHI effect. Cherry picking.

If there was any grain of truth in Gavin Schmidt’s ridiculous claim that the station dropout has no effect at all on the trends, he would have provided a link to such an analysis. Even more absurd is his statement that D’Aleo knows this.
Pure disinformation indeed.
If any of this were true, NASA or NOAA or anyone else could show results for rural, continuously run stations and all the complaints and objections would melt away.

I always chuckle when Steve uses those ironic parentheses such as here: “In my opinion, Gavin’s own statement that “urban heat island effects are corrected for in the surface records” is, to borrow a phrase from realclimate, “disinformation”.

#61. Gavin’s “answer” to your question merely shows that he is unfamiliar with the topic. The NOAA webpage that he referred you to is for USHCN v2. USHCN adjustments only apply to, in NASA’s phrase, “less than 6% of the earth’s land surface”. Even if the new USHCN adjustments “corrected” for UHI in the US, this does not permit Schmidt to claim, as he did, that corrections had been effected by NOAA on the other 94% of the earth’s land surface.

Second, USHCN v2 is very new. I don’t know exactly how their changepoint analysis works, nor is their algorithm available for detailed inspection. The enormous difference between NOAA US and GISS US suggests to me that this hot-off-the-press methodology is not accomplishing a UHI adjustment within the US – or else its result would look more like GISS US. For an algorithm to “correct” for UHI, it has to do what it says it does. I’m very doubtful that USHCN v2 methods areadequate, but the methods are new, poorly documented and it will not be a small enterprise to decode.

As to the other lines of evidence – glaciers, oceans: I’m not suggesting for a minute that it’s not warmer now than in the 19th century. I’m satisfied that it is. Glaciers in the Canadian Rockies in the 19th century were at their greatest extent since the LGM and have retreated. That is irrelevant to whether the temperature indices have “corrected” for UHI as Gavin claimed.

Nor do Parker’s articles demonstrate that the temperature indices have “corrected” for UHI. PArker’s articles argue that such an adjustment is unnecessary based on (IMO) highly questionable comparisons between windy and non-windy data derived from NCEP. Since people can observe large UHI in places where there would not have been a similar UHI in the 19th century, articles like Parker’s “proving” that the effect is negligible are going to fall on many deaf ears. I, for one, think that there’s something wrong with Parker’s analysis and have discussed it here in the past.

Oceans also seem to have warmed, but there you get into the bucket adjustment debate. Whatever the merits of these records, they don’t demonstrate that UHI is “corrected” for in the major indices.

Whether or not the “correction” makes a substantial difference in our understanding is a different issue. But there’s no need for Gavin to go a bridge too far by saying that UHI is “corrected” for in the temperature indices.

Steve Thanks for the extensive answer to my question #167 on RC. Apart from that I asked a few others and also said quite truthfully that I was a biochemist/molecular biologist. For this I was called a liar and my other questions citing specific references were dismissed either by stating the findings in the references I gave were wrong and/or that I was unable to comprehend the explanations given by others on RC. It was my first venture onto the site but they don;t want anyone there but sycophants who question nothing and accept anything that supports the concept of AGW

Suppose we could cover the world over with a temperature sensor every square kilometre. Better still, every 0.25 square kilometre. There are two choices for height ( mountains and hollows) a) ignore them and place the grid as if the earth were uniform, b) take real area, which will increase the surface of the earth. I say that if we had such a grid of measurements, the UHI effect would be irrelevant, in the sense that deserts and mountain tops etc would also be in the integration. If we had such a measuring grid we could get a well defined average world temperature with minimum corrections ( which is what the satellites are approximating).

My point is that in the absence of such a fine grid, one should place the measurement locations according to the well studied rules of polling: Decide on the number of types of environment: urban, desert, mountain, iceberg,tropics, etc and weight the results according to the percentage each of these types have on the surface of the globe. No UHI corrections will then be necessary,and the results will be valid if the rules of statistics are adhered to.

Re: anna v (#81), If we establish a new grid of weather stations, all you say might be true, but to go back and retrieve past temperatures, we are stuck with existing sites, which are subject to UHI, station moves, instrument changes, etc.

If the surface project of Anthony finishes, which will take some time in checking over the world, and a respectable number of good stations is found, one could use the logic of polls for corrections, i.e.weighting by representative area, rather than urban etc corrections. There will be a time dependence of the weights because of changes of land use.

The ocean temperature maps show that we could have maybe five bands in latitude, and within those, have “ocean”, “mountain”. “desert”, “forest”,”steppes”, “urban” etc. Find existing good stations in each of the fifty or so categories, how much area there is in each category, and go on from there.

Re: anna v (#96), Data are available from http://www.wunderground.com/ or through Mathematica 7.0 or via WMO data (R scripts & links around the site here somewhere). It is a tedious task to locate stations, verify the metadata, check if urban or not. It would be great if someone did it.

Yes, it would be a good task for a student, or a diploma thesis. My analysis tools ended with Fortran, I am afraid, and barely started with C++, when I retired in 2000. Old dogs can maybe learn new tricks but it would not be cost effective :)

Steve #74. When I wnet to NCDC last year, I got details on the USHCN2, I’ll see if I can find them and post here later. I recall that it completely misses long period data change, such as UHI, but detects short period events, such as a station move.

This is just nonsense. Of course air temperature one place impacts anything affected by temperature anywhere else.

simply brought up to make people think there is something wrong. The UHI effect is real enough, but it is corrected for – and in any case cannot effect ocean temperatures, retreating glaciers or phenological changes

The UHI effect is certainly real, “corrected for” or not. There’s plenty of reasons to bring it up other than the somewhat funny notion of making people think something is wrong, which is also immaterial in any case.

There is no possible way dumping waste heat and substances into the atmosphere doesn’t impact every part of the weather and climate systems. Aren’t these the same people telling us that there are teleconnections and that the human produced greenhouse gases are well mixed?

Steve: the link I provided is about lakes, both with long (more than a century) and short (since the 1980s) trends. No bucket temperature measurements involved. It’s all about observations of when the lakes freeze up and thaw. The rurality of the lakes (check the maps) indicate the UHI is an unlikely contributor to their trends. And it’s about the statistical analysis of that data, which I thought might interest you. Because if the trends are REALLY real, then they are good phenological indicators of regional climate changings. (Or something like that).

For those lakes that have data up until the last few years, there clearly is a diversity of recent freeze/melt times for the lakes, but there is no obvious demonstration of a systematic later freeze/earlier melts which supports the claim in the IPCC SPM.

Indeed, the variation between years and locations is expected, since as shown in

The PDF presentation cites Jenson (might be Jensen), Benson and Magnuson et al. 2007 and Benson et al. “in progress”. The presentation doesn’t have references, so someone would have to check to see if they cite Pielke Sr. or not. Plus, that paper is about heat/cold wave frequency, not trends in freeze-up or spring thaw dates.

Since ice in winter is pretty darned important to Canadians (as well as Gophers, Badgers, and Wolverines), I thought Steve might be interested. Lakes might be decent regional integrators. Bet they thaw later this spring!

“The Government should not keep information confidential merely because public officials might be embarrassed by disclosure, because errors and failures might be revealed, or because of speculative or abstract fears,”

They want to change the burden of proof from the person making the request to the officials in charge of the information and “adopt a presumption in favor”.

I’m sure this won’t prevent all resistance, but it establishes an encouraging tone.

This does not prove that CRU and NOAA estimates are any good. Quite the contrary. It shows that the CRU and NOAA failures to make UHI adjustments along the lines of GISS are introducing a substantial bias in these records

I’m a little confused on this point. Your trend plot shows GISS with a positive .39C/century bias compared against CRU and NOAA. As I am understanding it this bias exists as GISS is currently adjusting their data for UHI effects. The presumption in my mind is that UHI adjustments would always adjust temperatures lower as urbanization does not act as a cooling influence on the planet. Wouldn’t this mean that GISS is doubly wrong as their UHI compensaion is actually making their readings increase faster and CRU/NOAA are probably more realistic? Is there something I’m missing here?

#83. Anthony, for my purposes, I need to be able to work through calculations i.e. inspect what they actually do. It’s also necessary to place the method in a statistical perspective. This isn’t all that easy with many climate science articles as the methods are often ad hoc. A PPT from the workshop may be interesting but isn’t likely to give the required details.

Bernie (#54): I am waiting to hear back from the Office of the Attorney General about my allegation of fraud (as discussed on that page). It seems likely that the OAG is too busy to act on this, but not impossible; so I want to test it out. I have recently had some success in Sweden, via the judicial system, and I am encouraged by that.

Re: Mark Wilson (#100)
Sea surface temperatures are not rising as fast of land temperatures. In fact, there has been no measureable warming in the southern hemisphere for the last 30 years (CA has a post on this if you want to look). The lack of warming is attributed to the effect of the oceans in the SH but it could also be the result of less UHI bais in the SH because of the larger ocean contribution.

We really should do this station by station and country by county basis somehow. Classify the stations and the data on their reliability(if that is the right term). In Finland we also have reliable temperature data that is showing very little warming and warm 1930’s. I think it is no coincidence that Giss gets high “ROW” warming contrast to USA (or Finland or some other country with good data regards to UHI). I don’t think this can be proven yet, but the indication is clear: the more reliable the data, the less (local) warming! You add up the locals and it is considerably less global warming, i.e. the whole basis of the catastrophic warming theory questioned.

I think Gavin knows this deep down that is why he mentions “ocean temperatures, retreating glaciers or phenological changes”. The implication is that even if (you think) the surface data is a mess, there is other proof so it doesn’t matter. Now is that other evidence any more reliable?

Some people are trying to wring more detail out on a “country by county” basis (I like that typo – we once had a boss we called the Count with the silent O) & it is not all that easy. Some people and departments regard knowledge as being in their possession and they ain’t going to release it unless by force. In Oz land, if you ask for even a correction to an error, you can be told that a fee will be applied for “cost recovery”. A CD of data that costs under $5 to make is sold for $100 plus, presumably as a deterrent to gifted amateurs.

Many people agree with you that it should all be out in the open, but then we all know about bureaucratic obfuscation. As Sir Humphrey noted, “Anything is possible, but nothing is possible for the first time”.

I’ve had a chance to look at it more carefully, and it does seem to use it’s share of “processing” to make a point (not to mention the neat “Algoresque” figure implying Wisconsin will look like Arkansas by 2095). But be that as it may, can you shed some light on some questions I had while perusing it?

slide 3: Why the drop in ice duration from 1900-1950 relative to 1850-1900?

slide 7: Might this slide suggest that the “ice-off” date trendline since 1980 is dominated by the 1998 el nino?

slide 17: Why does the break-up date trend earlier from ~1880-1920 even though the temperature is trending colder?

slide 24: AGW started in 1800?

For those who prefer browsing “raw” data, click on a few of these graphs that Pielke Sr. linked to in his blog about lake ice (referenced in my comment above.)

Interesting graphs but short records on most. Are you aware of any studies using “ice on/off” as temperature proxies? I realize they are only annual dates, but they would show a trend. I can’t imagine a more non-controversial indicator of temperature change.

I’m only aware of the “PowerPoint” presentation and Pielke Sr’s take on the issue. It would be interesting to see a straightforward analysis of the data without resorting to statistical gymnastics (google Coherent Dynamics and the top hits are related to quantum mechanics). Perhaps the PowerPoint presentation will yield a paper that fits the bill, but the slides seem to show a lot of data “intervention”.

As far as longer term data, the web page I linked to has quite a few lakes and bodies of water with data going back more than 50 years (Callander Bay/Lake Nipissing, Chemong, Churchill River, Couchiching, Head). Granted, these are all Canadian (who can believe those?). :)

Perhaps most of them are too far North to approach Arkansasian conditions yet.

Enamored? No. Intrigued, yes. One of my hobbies is birdwatching (not obsessional, just when the opportunity presents). I’ve been fascinated by all aspects of climate change, particularly those that relate to alteration of biomes and migrations. So the ongoing issue of surface temperature records vs. the trends of the natural enviroment is always of interest. Thus the third quote of Gavin caught my attention.

So, being unrelated to the studies other than by interest, my comments in regard to your questions will be necessarily speculative. But I’ll do my best.

slide 3: Why the drop in ice duration from 1900-1950 relative to 1850-1900?

I’d have to think a warmer climate in 1900-1950 compared to 1850-1900. Seems like that’s been attributed to three things: exiting the tail end of the Little Ice Age, a slight increase in solar activity, and increasing atmopheric CO2. Have you heard of Delworth and Knutson 2000?

slide 7: Might this slide suggest that the “ice-off” date trendline since 1980 is dominated by the 1998 el nino?

I wouldn’t think that’s the whole story, because the ice-off dates are considerably post-1998 than prior to 1998.

slide 17: Why does the break-up date trend earlier from ~1880-1920 even though the temperature is trending colder?

Let’s clarify this. Based on the right side of the graph, the breakup anomalies trend negative as “Spring N. Hemisphere temperature anomalies” trend positive. (As expected.) From 1870 to 1910, the spring temperature anomaly decreases from about -1 to -2. At the same time, the breakup anomaly is decreasing. According to the standard story, climate was just starting to warm late in the 19th century. If that’s so, we don’t really see a shift caused by this in the spring temperature anomalies until 1910 or so. But the lakes may have been responding to the slight warming, and also to pretty big land-use change: the boom in Minnesota logging took place from 1890 to 1910. From 1910 to 1950, the spring temprature anomaly goes from -2 to 0; about twice the reverse rate of the previous 40 years. Breakup anomalies continue to decrease (with obvious variability). Then there’s a flattening of both trends in the well-known 1950s to 1980s cool period. Then warming and increasingly negative breakup anomalies.

So it looks like there’s a few effects going on in the period you asked about.

slide 24: AGW started in 1800?

Looks like they overlapped the earlier trend end year and the later trend start year at what looked like a good transition point. I wouldn’t argue that AGW started in 1800, but signficant land use change in Japan probably started well before it started in North America. Since the graph says “preliminary”, it’s worth watching.

Your questions are fun. Anyways, I’m interested in how much we can learn “from nature” compared to how much we can learn from the flawed instruments and techniques of man, and how much we should believe both of them. Based on Steve’s ongoing campaign, I think nature should at least be refered to for a basis of comparison!

I think my point was (in an admittedly obscure way) that sometimes climate scientists try to read WAY to much into their anlalysis of uncertain data. Those trends I focused on may simply be that the data have uncertainty and the decrease or increase in any particular time period is simply within the margin of error.

But I and most folks that frequent this blog would agree with you that land use changes are important considerations in trying to decipher the Earth’s temperature and climate history.

Compare Slide 11 in the Powerpoint to the map of the IceWatch locations. To get to the latter, click on “View Results” and then on “Click here to create maps of IceWatch observations across Canada”.

Thus, regarding your comment in #117: I think you’re right. The most observable trends in “ice-on” and “ice-off” are occurring further south than the majority of the IceWatch lakes. I think I’m going to have to leave that to the climate scientists to explain.

Is there really a question if seven billion people’s cities and activities have anything other than a major impact upon the weather worldwide? A trend of a few tenths of a degree over decades is hardly a surprise, is it?

Perhaps it’s time to step back and rethink getting caught up in bickering over the minutia of the surface temperatures, or that they’re important other than a rough large scale average.

Sam, While agreeing generally that more people might cause some global warming, there are imponderables like – if not people, then maybe termites would populate the earth, belching methane. Or, Man interfering with vegetation would have very little efect because grass would grow and decay to GHG irrespective of Man. Just because man is present, it is not axiomatic that global effects are maximised to the worst. Heat from the combustion of fuels would seem to be the main factor aiding your point. I’m not disagreeing with you, just adding some caveats.

Is there really a question if seven billion people’s cities and activities have anything other than a major impact upon the weather worldwide? A trend of a few tenths of a degree over decades is hardly a surprise, is it?

Sam, the answer is clearly no, “seven billion people’s cities and activities” have little more impact upon the weather worldwide than they do upon the speed of the Earth’s rotation or the mythical notion that China’s massive population could have a worldwide impact by simultaneously jumping off a two meter high platform. The Earth’s climate system has a mass, energy, and inertia little understood or appreciated by most people, including most scientists. As impressive as humanity’s capacity for causing environmental modifications appear to be at first glance, they pale into insignificance besides the influences and counter-influences of the lowliest of lifeforms. It remains to be demonstrated how anyone in their right mind could assume without solid proof that humans have the capacity to halt the warming of the inter-glacial period in which we presently exist, hope to halt the next and inevitable multi-million year ice age, or halt the inevitable warming of the entire planet as the Sun continues to increase its luminosity towards becoming a giant star.

Even if we accepted the notion it was vitally necessary to apply the precautionary principle, assuming it is necessary to take precautions against a warming of the world climate makes no sense whatsoever. The Earth is presently at the extreme low end of the life zone scale for temperature and carbon dioxide in the atmosphere. The Earth is typically around 10C warmer and 5X to 20X more carbon dioxide for the past 600 million years than it is now, despite a lower Solar luminosity. The present global temperature levels are only about 1C to 2C above Earth’s lowest ever air temperatures, and the carbon dioxide levels are comparable to the lowest ever carbon dioxide levels to within a fractional part of the present levels. During the past 600 million years, the Earth has experienced great extinctions of major fractions of the planet’s species of life whenever the present conditions and slightly lesser temperatures and carbon dioxide levels occurred.

In other words, the Earth is presently only about 1C to 2C cooling and 150ppm of lesser carbon dioxide away from a planetary biospheric catastrophe, and it is 10C to 12C of warming temperature and 1500ppm to 1600ppm of more carbon dioxide away from reaching Earth’s normal and beneficial conditions for optimal diversity of life. We know this to be true from vastly long experience.

Consequently, anyone seriously worried about taking the precautions mandated by an application of a precautionary principle must look at preventing the colder temperatures and lower carbon dioxide levels which have always resulted in catastrophic extinctions of 40 percent, 60 percent, or even 90 percent of all species of life on the Earth.

Perhaps it’s time to step back and rethink getting caught up in bickering over the minutia of the surface temperatures, or that they’re important other than a rough large scale average.

Adversely displacing a great fraction of humanity’s global economies for the sake of an erroneous and imaginary problem, or an actual problem whose progress cannot be significantly affected, or significantly affecting an actual problem by making it colder and worse instead of warmer and better can hardly be regarded as “minutie.” If the temperatures were minutia, the IPCC leadership and others would not be making such controversial and heavy handed efforts to manipulate and reverse the findings of some contributors to the IPCC reports. Science matters, especially when appealing to the application of a precautionary principle which may result in irrationally and blindly jumping into self-inflicted famine and/or hypothermia and extinction.

So, it matters not whether a person chooses to assume precautions must be taken in advance of scientific proof by a preponderance of the evidence or otherwise. If humanity could have an effect upon global climate events at all, it still does no good to destroy world liveliehoods for the sake of making matters worse by implementing good intentions which prove to be horribly fatal mistakes.

So long ss the IPCC insists upon claiming that the temperatures are sufficient cause to assume the world economies must be seriously damaged to take precautions, it will be vitally neessary to evaluate the IPCC’s reports and conclusions using proper and valid scientific methods.

I can’t help but think that if sea levels were rapidly falling, we’d be hearing the same kind of alarmism. And of course people would start building on the newly formed land, creating more of a problem when sea levels came back.

Of course 700% more people than pre-1800 in and of itself isn’t going to do anything much. Or at least one imagines their weight and breathing wouldn’t make much of a difference. Although I’ve not seen anything peer reviewed on that….

It’s their cities, farms, cars, ships, airplanes, factories, power plants, and the like. Everything needed to support the numbers and the side effects of the technologies that do. Even if it were possible to put everyone in unlighted, unheated, uncooled shacks and allow no personal travel by energy powered machines, just the infrastructure required to produce and distribute enough food to support the numbers would have an impact upon the weather that would be more than inconsequential. But you can’t even fit 7 billion, much less support them, without everything else that goes along with it.

And everything we do impacts the land, the air and the water. New York or Los Angeles don’t just sit there and not impact the water surfaces around them, especially with all the ships and aircraft coming in and out of them. Multiply that by hundreds or thousands.

Most everything else you bring up I didn’t even mention. All I said is that you’d expect some minor change in the metrics (rough estimates of “global average temperatures”) with all the people and their stuff. And that we should focus on these supposed problems and their suggested solutions rather than details of the samples themselves.

Hello Sam, in short, it has long been my understanding that anthropogenic impacts are negligible to the extent that measurements can hardly separate the impacts from the minute instrumental errors. That is another reason why the metrics, small or not, are significant. I’ll explain that and expand on it later tonight. I’ll have more time then. Global Warming is forecast to favor us with about 5 to 8 inches of snow tonight (smile).

D. Patterson, I don’t think we’re having the same conversation. But seriously, 1800 ppmv and/or 22 C as a perfect and natural and historical level? Regardless, that’s not pertinent here. (Correlating those is a different subject entirely of course, also not pertinent here.)

Sam, it is highly pertinent to the question you asked.

Is there really a question if seven billion people’s cities and activities have anything other than a major impact upon the weather worldwide?

It’s unfortunate that you cannot see and understand how the pre-human climates of the Phanerozoic are highly pertinent to understanding the limited scope of human influence upon the climate of the past century or so. Human influences upon the global climate are not unique for this planet’s past climates. Likewise the artificial UHI effects are not unique in our planet’s existence, becuase there have also been natural heat island effects as well. I’ve seen little evidence of a proper discussion or understanding of the UHI or the natural heat island effects with respect to accurate measurements and post-measurement adjustments. Instead, I have watched in dismay as the leadership of the WMO in the Seventies and its subsequent offspring, the IPCC, engage in mismanagement of data collection and dubious manipulations of the raw and analyzed data for the past 40 years. I have personally witnessed the falsification of synoptic observations at international airports while I used the identical instrumentation. There are many other official and anecdotal reports of errors entereing the data record as a result of instrumental errors, misconduct, and more. Like the arbitrary UHI ajustments, these sources of error are disregarded altogether, subjected to arbitrary adjustments without adequate experimental verifications, and generally denied as a confounding problem in the preparation of the IPCC reports and conclusions. Consequently, I cannot ignore what I have witnessed, and I cannot have confidence in the IPPC reports or the sources of the IPCC unless and until such time as these errors and problems are corrected by a means which is rational and verified by proper independent replications of the necessary scientific experiments. Furthermore, digital modeling is not a substitute for proper physical scientific data and methods.

Although it’s all pretty much just opinion backed by circumstantial or anecdotal evidence and models, it is the scientific opinion that:

increases in anthropogenic greenhouse gas concentrations is very likely to have caused most of the increases in global average temperatures since the mid-20th century

Yes, the problem is that you need to ask who’s “scientific opinion.” Despite the press releases of James Hansen, Gavin Schmidt, Michael Mann and others claiming the debate is over, there are a large number of of scientists who are no less qualified and are more qualified in climate science and the atmospheric sciences who strongly dispute such claims. Hansen’s former superior for one such example, Dr. John S. Theon, has recently added his voice to dispute the conclusions and the conduct of Hansen and the IPCC. UHI is a very real scientific phenomenon, and Gavin Schmidt is misinforming his listeners when he claims UHI has been adjusted out of the climate datasets. Worse yet, the falsified raw data in the records is not even being acknowledged, much less discussed, in any meaningful way with respect to the validity of the IPCC reports and the studies used to prepare those reports. How can anyone expect to obtain valid results using fictional data with persistent biases?

If you want to test Gavin Schmidt and the IPCC reports he uses to support his claims, try to obtain proof that the datasets have been adequately adjusted to remove the false raw temperature observations used in the preparation of the various models relied upon by the IPCC. I’ll bet he uses one of the NWS or other studies which claims the errors from the erroneous observations are negligible and not a significant factor in the error range of the climate models. I’ll also bet the claims of negligible impact cannot be verified by independent researchers, because the actual scope of the errors is unknown, unknowable, and undeterminable. Suffice it to say that whatever the impact of the errors may be, they are highly likely to be greater in potential effect than the adjusted temperatures and change rates being reported by GISS, UCAR, and the IPCC. In other words, the range of measurement errors are highly likely to be greater than the alleged temperatures. Evidence of this problem has been seen time and again on this blog with the various analyses of the ROW observations as just one category of examples.

Sam, I cannot help but observe that you are premature in making presumptions about the anthropogenic effects upon the world’s climate, despite its obvious impacts upon geography and the biosphere. You should especially note that human impacts are not necessarily undesirable for humans or the biosphere. You may even want to consider the possibility that anthropogenic warming of the planet is a necessity for the survival of humans and most species of the biosphere.

[Aren’t there enough known rural sites in the network to allow the discarding of obviously urban stations so as not to have to worry about “adjustment” for UHI? The fact that “urban” stations are included for purposes of global climate monitoring seems rather dim-witted when there should be plenty of rural, or at least less urban, stations relatively nearby.]

I have always wondered why they use station pairs to extract the UHI effect from the urban sites, why not use just rural, I am sure at least for the U.S a couple of hundred good quality rural stations equally spread will give a more accurate trend than the present setup.

The best argument to make is the most conservative one, which is the argument that Steve is making. Otherwise, your “opponent” will focus on the weakest link in your position and ignore everything else. JohnV demonstrated here sometime ago, working with top-rated stations (rated by surface-stations), that GISS does a reasonable job of adjusting for UHI and Steve seems to agree in this post.

Were these top rated stations rural as it appears any time a rural only study is undertaken there is little or no warming, odd that.

D. Patterson, I don’t think we’re having the same conversation. :) But seriously, 1800 ppmv and/or 22 C as a perfect and natural and historical level? Regardless, that’s not pertinent here. (Correlating those is a different subject entirely of course, also not pertinent here.)

In that context, it’s disinformation (is is that disingenuous) to say UHI has no effects.

I also should have said the minor changes in the metrics we see supposes they aren’t due only to changes in sampling methods, equipment and calculations. We’re also supposing that all the carbon dioxide equivalent and waste heat we produce have a net impact upon the system. I think both are reasonable suppositions, given the small numbers we’re talking about in the anomaly. And the obvious physical changes on the planet since, say, 1900.

Although it’s all pretty much just opinion backed by circumstantial or anecdotal evidence and models, it is the scientific opinion that:

increases in anthropogenic greenhouse gas concentrations is very likely to have caused most of the increases in global average temperatures since the mid-20th century

Does this all mean the only “solution” to the “problem” is a return to pre-industrial times? Probably. Again, not pertinent here.

The point being that UHI is hardly some mystical minor unrelated issue when it comes to climate change.

Re: Sam Urbinto (#127), The main effect causing UHI is the change in albedo when vegetation is replaced with asphalt and buildings. It is not that it warms the whole world, but that it warms the area where the weather station is, and that as the city grows the warming gets larger, thus creating a time-trend that looks like global warming. Large-scale land-cover change like forest into agriculture is a very different issue due to its extent, and can warm or cool, depending on what it is. Pielke sr has lots on this.

Craig: I contend the effects of UHI can’t be considered as some monolithic quality with a discrete quantity, but rather in the context of effects that are far more reaching, once everything is considered. It may be that UHI in and of itself is minor, or that the direct effects are only the bias upon the sampling, known or not, corrected or not.

On that topic, my point would simply be that to say there are nothing but “local effects” of an area (for example, one the size and location as metro LA or Miami/Dade) seems to simply disregard the entire weather system as a whole. Perhaps it’s more correct to discuss LULC as the subject, with UHI an important part.

FWIW, I agree that using the anomaly as a proxy for energy levels is rather a case of using what we have rather than something of real use. In that context, then perhaps UHI “doesn’t matter” and it’s “time to move on”. Physical laws, observable phenomena, models, samples, and anecdotal/circumstantial evidence being beside the point in that case.

I suppose the key here is defining the subject and the metrics to use with it. Some clearly defined ground rules, so to speak.

I should say, UHI as one of the many impacts of human civilization upon the ecosystem. Along with the usual difficulty in climate related matters with generating the specifics.

But just as an example of what I mean about the entire subject, this simple explanation for the Arctic “warming faster than the rest of the globe”

Industry, transportation, and biomass burning in North America, Europe, and Asia are emitting trace gases and tiny airborne particles that are polluting the polar region, forming an “Arctic Haze” every winter and spring. Scientists suspect these pollutants are speeding up the polar melt.

Suspect? What else is causing it, dumping chemicals into the ocean off the coasts of Brazil, Tanzania and North Carolina USA? Strip mines in Paraguay, Tajikistan and Katherine Australia? Building roads in Rosetown Saskatoon Canada and Jeonju North Jeolla South Korea? Perhaps all the cows in Miyun Beijing China. It’s just plain crazy! :)

Last night at 22:30 we drove home from Cheltenham town centre temperature +2.5C. 1km towards the urban edge the temperature was 0C 17km further from the town the temperature was -2C

This morning 08:15 drove to work temperature was 0C, 17 km into Cirencester town centre temp was 0C
(look the places up on google if you need)
This morning 07:45 my wife drove to cheltenham where the sreets were paved with ice (do not know the temperature but obviously lt 0C)

Obviously the concrete of cheltenham retains the days heat but eventually cools UHI effect must be partially a phase shift?
How can you allow for this sort of UHI?
If urbanisation happens then surely there would be discontinuities showing within a few weeks of readings as the roads are built then the houses constructed? Shouldn’t these be visible on the temperature plots?

If the urban area is at a different temp to surroundings then there should be the equivalent of sea breezes modifying the site environment.

How do you account for wind speed?
How would you account for wind direction?

I didn’t really ask any questions about levels of atmospheric gases or average temperature.

The rhetorical questions were a statement that seven billion people’s cities and activities have an impact upon the weather worldwide, major in the sense it’s observable and the source is known. The other side of my observations were that it’s hardly surprising if the anomaly trend over time is upwards a few tenths of a degree. Regardless of the reason(s). Neither of my comments attempts to qualify things, nor even establish a relationship between the effects on the weather and the anomaly. It also isn’t a commentary on the state of science, the importance of the recent trend rise in the anomaly, or what, if anything, needs to be done about it.

I believe I’ve been clear in the past I’m of the opinion that the anomaly trend is just as likely due to changes in measurement and/or processing. Or is well within the margin of error of the readings or averaging of them, or is due at least partially to bias(es), etc etc.

I’m simply saying that “UHI” shouldn’t be ignored and that it’s not inconsequential.

Your comment on the Phanerozoic. What does the physical status of the Earth 40 or 200 MYA have to do with the most recent few hundred or thousand? But if the point is that Earth has had many major changes without humans, of course it has. No humans were required to produce the Eemian, right? And we probably had nothing to do with Lake Agassiz draining. :)

The point is that in our most recent little slice of the Subatlantic, there have been certain changes to the climate we’ve observed. In the absence of some large change in the short period of the last two or six or eight or eighteen-hundred years in Earth’s {orbit, core, magnetic field, insolation, axial tilt, etc}, there’s a simple explanation for any part of the behavior that is actually due to anything other than noise et al. And I’m not trying to qualify or quantify anything, just point out there’s a simple explanation; an observable one.

Like the arbitrary UHI adjustments, these sources of error are disregarded altogether, subjected to arbitrary adjustments without adequate experimental verifications, and generally denied as a confounding problem in the preparation of the IPCC reports and conclusions.

Which is one of the reasons I commented that all we have is a general rough estimate of how things probably are. The specifics are uninspiring and unimportant; a distraction.

Let’s break down the conclusion about humans and heat while we’re at it!

Industrial era increases in levels of LW IR reactive gases seem to be probably responsible for the bulk of any change in the planet’s energy levels since that time. We happen to believe the anomaly trend probably reflects such changes. The trend is up, so it looks like that means it’s warming. A lot of this is conjecture and opinion of course. But we’ll phrase it in the appropriate manner, don’t worry.

lol

How can anyone expect to obtain valid results using fictional data with persistent biases?

I don’t know if I’d call it fictional, or try and qualify what is valid or invalid. But it is all taken into consideration, assigned a place in the scheme of things, and then the details jettisoned so more important things can be focused upon.

In other words, the range of measurement errors are highly likely to be greater than the alleged temperatures.

Of course they probably are. That’s why it’s a general rough estimate and not specific pinpointed fact. !

Sam, I cannot help but observe that you are premature in making presumptions about the anthropogenic effects upon the world’s climate, despite its obvious impacts upon geography and the biosphere.

That waste heat and ground and atmospheric by-products of producing it, along with the roads, farms, buildings, parking lots and the like, all are their own evidence. As far as the impacts, the only solution is probably a return to pre-1700 population, industrialization and urbanization. And that assumes the net sum of other physical changes aren’t the bulk of the difference. If there is actually a difference.

Again, I point out that “Industry, transportation, and biomass burning in North America, Europe, and Asia are emitting trace gases and tiny airborne particles that are polluting the polar region, forming an “Arctic Haze” every winter and spring.”

You should especially note that human impacts are not necessarily undesirable for humans or the biosphere. You may even want to consider the possibility that anthropogenic warming of the planet is a necessity for the survival of humans and most species of the biosphere.

Pointing out that LULC explains everything in a simple and obvious way isn’t a comment on if human impacts might be good or not. Immaterial. It doesn’t even deal with it. This is about UHI. And that the claim that UHI effects are corrected for is probably a mistaken belief.

As Steve said

This does not prove that CRU and NOAA estimates are any good. Quite the contrary. It shows that the CRU and NOAA failures to make UHI adjustments along the lines of GISS are introducing a substantial bias in these records.

Or even more to the point

Whether or not urban heat islands have a material impact on the surface records is a different question. The difference between GISS US results and NOAA US results is strong evidence that there is a noticeable impact – one which needs to be addressed by CRU and NOAA and by GISS outside the US. In my opinion, Gavin’s own statement that “urban heat island effects are corrected for in the surface records” is, to borrow a phrase from realclimate, “disinformation”.

I love it when people throw out huge population numbers (7 Billion) to illustrate mankind’s impact on the land, oceans and atmosphere. I swear, they all must live in the city and think the whole world is cramped and polluted.

People really need to get out more and see how open and uncrowded the planet realy is and how insignificant a cow fart really is.

I love this little factoid: The entire world population would fit into the State of Texas, with a little room to spare.

[…] Neither CRU nor NOAA have archived any source code for their calculations, so it is impossible to know for sure exactly what they do. However, I am unaware of any published documents by either of these agencies that indicate that they “correct” their temperature index for UHI effect (as Gavin claims here) and so I’m puzzled as to how Gavin expects D’Aleo to be able to “know” that they carry out such corrections. And as to GISS adjustments, as we’ve discussed here in the past (and I’ll review briefly), outside the US, they have the odd situation where “negative UHI adjustments” are as common as “positive UHI adjustments”, raising serious questions about whether the method accomplishes anything at all, as opposed to simply being a Marvelous Toy. More » […]

[…] out the errors and AGW advocacy, rather than scientific quest, at realclimate – Steve McIntyrre realclimate and Disinformation on UHI Climate Audit Both sites have enough posts (even BEFORE the CRU E-mails pretty well established the realclimate […]